Respiratory Distress Syndrome, Adult Clinical Trial
Official title:
New Criteria for Classifying Acute Respiratory Distress Syndrome Severity Using a Machine Learning Approach: Novel Oxygenation and Saturation Indices
This study aims to determine the cut-off values of the new oxygenation indices and further investigate their capabilities in diagnosing ARDS and predicting its severity in ICU. Additionally, the investigators aim to compare these results with conventional oxygenation and saturation indices.
Recent studies have shown that mechanical power (MP) values below 17 J/min and driving pressure (DP) values below 15 cmH2O reduce intensive care unit (ICU) mortality. Asar et al. have introduced six new oxygenation indices utilizing MP and DP instead of Pmean (OSI-MPtot, OI-MPtot, OSI-ΔPinsp, OI-ΔPinsp, OSI-MPdyn, OI-MPdyn). They compared the predictive abilities of these new indices for ICU mortality in Covid-ARDS (C-ARDS) patients with conventional oxygenation indices (P/F, SpO2/FiO2, OI, OSI, PaO2/(FiO2xPEEP), and SpO2/FiO2xPEEP). OI-ΔPinsp, OSI-ΔPinsp, and OSI-MPdyn indices exhibited the highest predictive power for ICU mortality. However, cut-off values for the diagnosis and severity determination (mild, moderate, and severe) of ARDS patients have not been investigated. In this study, our objective is to determine the cut-off values of the new oxygenation indices and further investigate their capabilities in diagnosing ARDS and predicting its severity in ICU. Additionally, the investigators aim to compare these results with conventional oxygenation and saturation indices. ;
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